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Global optimality conditions and optimization methods for constrained polynomial programming problems

Author

Listed:
  • Wu, Zhiyou
  • Tian, Jing
  • Ugon, Julien
  • Zhang, Liang

Abstract

The general constrained polynomial programming problem (GPP) is considered in this paper. Problem (GPP) has a broad range of applications and is proved to be NP-hard. Necessary global optimality conditions for problem (GPP) are established. Then, a new local optimization method for this problem is proposed by exploiting these necessary global optimality conditions. A global optimization method is proposed for this problem by combining this local optimization method together with an auxiliary function. Some numerical examples are also given to illustrate that these approaches are very efficient.

Suggested Citation

  • Wu, Zhiyou & Tian, Jing & Ugon, Julien & Zhang, Liang, 2015. "Global optimality conditions and optimization methods for constrained polynomial programming problems," Applied Mathematics and Computation, Elsevier, vol. 262(C), pages 312-325.
    • Handle: RePEc:eee:apmaco:v:262:y:2015:i:c:p:312-325
    DOI: 10.1016/j.amc.2015.04.040
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    References listed on IDEAS

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    1. Vaithilingam Jeyakumar & Zhiyou Wu, 2007. "Conditions For Global Optimality Of Quadratic Minimization Problems With Lmi Constraints," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 24(02), pages 149-160.
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    Cited by:

    1. Wang, Jianzhou & Dong, Yunxuan & Zhang, Kequan & Guo, Zhenhai, 2017. "A numerical model based on prior distribution fuzzy inference and neural networks," Renewable Energy, Elsevier, vol. 112(C), pages 486-497.

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